The code behind the title page map:

# Load libraries
library(terra)
library(viridis)
library(rnaturalearth)

# Query DEM data for Colombia
col_dem <- geodata::elevation_30s(country = "COL", path = tempdir())

# Query boundary of Colombia
col <- ne_countries(scale = 10, country = "Colombia")

# Plot the map to a png file
png("slides/figures/colombia-dem.png", bg = "transparent", height = 4, 
    width = 4, res = 300, units = "in")

par(mar = c(0, 0, 0, 0))
plot(ext(col_dem), lty = 0, axes = FALSE)
plot(col$geometry, add = TRUE, border = "#f1faee", axes = FALSE, box = FALSE)
plot(col_dem, col = magma(100), add = TRUE, axes = FALSE, box = FALSE, 
     legend = "bottom", 
     plg = list(title = "Elevation (m)", cex = 0.7, col = "white", lwd = 2, 
                title.col = "white", title.cex = 0.7))
dev.off()

Introduction

  • Time: Mon and Wed, 3:50 - 5: 10 PM
  • Lecture: Lucy Stone Hall (LSH-B266), Livingston campus
  • All course materials are hosted on its own site: https://sselp.github.io/sdawr/
  • Canvas will be used only for posting grades.

Communication

  • We will use Google Chat 450:230(SP2026) for all course-related communication.
    • Course announcements
    • Deadline reminders
    • Course readings, exercises and quizzes (these count toward participation!)
    • Asking questions and helping each other!
    • Direct messages for private conversations

Need help?

  • Google chat:
    • Arafat and I will do our best to respond to messages daily.
    • You are strongly encouraged to help and support each other.
  • Office hours:
    • Lei Song: Mon and Wed, 2:50 - 3:50PM (or by appointment)
    • Md Arafat Hassan (Your TA): TBD

Course Overview

  • By the end of this class, you should
    • Be comfortable in working with R, including most common spatial functions
    • Have a good sense of where R is headed as a language
    • Know how to seek help properly when don’t know how to do something
    • Be using R as part of a reproducible workflow

What is a reproducible workflow?

Reproducibility

Class Overview

  • Course approach
    • (Largely) flipped model and emphasis on problem solving
      • Programming should be fun! (or at least intriguing)
  • Basic policies
    • Attendance and communication
    • Attention to detail

Course Requirements

What you need to do:

Component Grade
Practical assignments (n = 5) 40%
Participation 10%
Overview for final project 10%
Oral defense for final project 10%
Final project 30%

Practical Assignments

There will be a quiz-based grade refinement for all assignments. Each assignment is followed by an in-class, closed-book quiz consisting of 10 questions directly related to the programming tasks you just completed. Your final score for the assignment will be refined by your quiz performance according to the following tiers:

Quiz Score Assignment credit
8-10 100%
6-7 85%
4-5 70%
0-3 60%
Miss 0%

Final Project

  • Project overview (10%)
  • Project oral defense (10%)
  • Final project (30%)
    • Presentation
    • Final report
  • Check details on the page of projects

More Details

  • Check our course Syllabus
  • Grading will be based on the rubrics found under the Assessment

Let’s Get Set Up!

  • Software installation
  • Very important! Install everything this week. If you run into any issues, don’t hesitate to ask for help.

Homework

  • Go to our course site to check everything.
  • Read Unit1-Module 1 before section 3.2.1, section 1.7 Style in Syllabus, and cheatsheet of RStudio and R markdown on the page of Cheatsheets.
  • Get yourself a GitHub account, if you haven’t
  • Send us your GitHub name (!!)
  • Install all necessary software on your local computer(s) if you haven’t today.
  • Set up your personal access token following section 2.1 in Git/GitHub).

Next Class

  • R package and R markdown.
  • Set up your package!